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ci: Constrain all dependencies
Signed-off-by: Ihar Hrachyshka <ihar.hrachyshka@gmail.com>
1 parent 0bb0f7e commit f6b9755

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‎.github/workflows/constraints-update.yml‎

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name: Update constraints-dev.txt
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on:
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schedule:
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- cron: '0 3 * * 1' # Every Monday at 03:00 UTC
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workflow_dispatch:
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jobs:
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update-constraints:
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runs-on: ubuntu-latest
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permissions:
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contents: write
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pull-requests: write
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steps:
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- name: Checkout repository
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uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
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- name: Checkout "update-constraints" in-house CI action
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uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
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with:
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repository: instructlab/ci-actions
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path: ci-actions
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# no tag that includes https://github.com/instructlab/ci-actions/pull/26, yet
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ref: 88641ccaf122964eacdc1a82b18bda369b6f99bd # main
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sparse-checkout: |
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actions/update-constraints
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- name: Update constraints
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id: update-constraints
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uses: ./ci-actions/actions/update-constraints
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with:
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gh-token: ${{ secrets.GH_PERSONAL_ACCESS_TOKEN }}

‎.github/workflows/e2e-nvidia-l4-x1.yml‎

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- '**.py'
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- 'pyproject.toml'
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- 'requirements**.txt'
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- 'constraints-dev.txt'
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- '.github/workflows/e2e-nvidia-l4-x1.yml' # This workflow
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concurrency:
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- name: Install ilab
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working-directory: ./instructlab
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run: |
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export CUDA_HOME="/usr/local/cuda"
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export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:$CUDA_HOME/lib64:$CUDA_HOME/extras/CUPTI/lib64"
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export PATH="$PATH:$CUDA_HOME/bin"
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python3.11 -m venv --upgrade-deps venv
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. venv/bin/activate
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nvidia-smi
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python3.11 -m pip cache remove llama_cpp_python
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pip_install="python3.11 -m pip install -v -c constraints-dev.txt"
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pip_install="python3.11 -m pip install -v -c constraints-dev.txt"
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# pre-install some build dependencies
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$pip_install packaging wheel setuptools-scm
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# flash-attn has a bug in the setup.py that causes pip to attempt installing it
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# before torch is installed. This is a bug because their setup.py depends on
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# importing the module, so it should have been listed in build_requires. Alas!
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#
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# See: https://github.com/Dao-AILab/flash-attention/pull/958
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# Also: https://github.com/instructlab/instructlab/issues/1821
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#
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# first, pre-install flash-attn build dependencies
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$pip_install torch packaging setuptools wheel psutil ninja
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# now build flash-attn using the pre-installed build dependencies; this will
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# guarantee that the build version of torch will match the runtime version of
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# torch; otherwise, all kinds of problems may occur, like missing symbols when
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# accessing C extensions and such
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$pip_install flash-attn --no-build-isolation
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CMAKE_ARGS="-DGGML_CUDA=on" $pip_install .
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$pip_install .[cuda] -r requirements-vllm-cuda.txt
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PYTHON=python3.11 ./scripts/install-ilab-with-cuda.sh
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- name: Update instructlab-eval library
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working-directory: ./eval
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run: |
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. ../instructlab/venv/bin/activate
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pip install -v .
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# Patch out our own pin from the ilab repo constraints file
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ilab_constraints=../instructlab/constraints-dev.txt
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sed -i '/instructlab-eval==/d' $ilab_constraints
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# Since we reuse the virtual environment prepared using ilab
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# constraints, we should stick to the same constraints when
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# installing latest eval.
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#
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# FIX: this is not ideal; a proper fix would require decoupling the
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# two repos in CI: either by removing the job completely and relying
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# on "sdk" (no ilab) test runs; or by preparing a separate
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# constraints file that would consider both the requirements files
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# for the eval library AND for the ilab - so that they are
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# consistent.
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pip_install="pip install -c $ilab_constraints"
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$pip_install .
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$pip_install .[cuda]
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- name: Run e2e test
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working-directory: ./instructlab

‎.github/workflows/e2e-nvidia-l40s-x4.yml‎

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- name: Install ilab
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working-directory: ./instructlab
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run: |
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export CUDA_HOME="/usr/local/cuda"
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export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:$CUDA_HOME/lib64:$CUDA_HOME/extras/CUPTI/lib64"
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export PATH="$PATH:$CUDA_HOME/bin"
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python3.11 -m venv --upgrade-deps venv
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. venv/bin/activate
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nvidia-smi
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python3.11 -m pip cache remove llama_cpp_python
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pip_install="python3.11 -m pip install -v -c constraints-dev.txt"
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# pre-install some build dependencies
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$pip_install packaging wheel setuptools-scm
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# flash-attn has a bug in the setup.py that causes pip to attempt installing it
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# before torch is installed. This is a bug because their setup.py depends on
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# importing the module, so it should have been listed in build_requires. Alas!
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#
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# See: https://github.com/Dao-AILab/flash-attention/pull/958
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# Also: https://github.com/instructlab/instructlab/issues/1821
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#
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# first, pre-install flash-attn build dependencies
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$pip_install torch packaging setuptools wheel psutil ninja
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# now build flash-attn using the pre-installed build dependencies; this will
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# guarantee that the build version of torch will match the runtime version of
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# torch; otherwise, all kinds of problems may occur, like missing symbols when
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# accessing C extensions and such
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$pip_install flash-attn --no-build-isolation
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CMAKE_ARGS="-DGGML_CUDA=on" $pip_install .
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$pip_install .[cuda] -r requirements-vllm-cuda.txt
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PYTHON=python3.11 ./scripts/install-ilab-with-cuda.sh
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- name: Update instructlab-eval library
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working-directory: ./eval
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run: |
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. ../instructlab/venv/bin/activate
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pip install .
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pip install .[cuda]
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# Patch out our own pin from the ilab repo constraints file
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ilab_constraints=../instructlab/constraints-dev.txt
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sed -i '/instructlab-eval==/d' $ilab_constraints
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# Since we reuse the virtual environment prepared using ilab
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# constraints, we should stick to the same constraints when
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# installing latest eval.
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#
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# FIX: this is not ideal; a proper fix would require decoupling the
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# two repos in CI: either by removing the job completely and relying
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# on "sdk" (no ilab) test runs; or by preparing a separate
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# constraints file that would consider both the requirements files
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# for the eval library AND for the ilab - so that they are
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# consistent.
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pip_install="pip install -c $ilab_constraints"
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$pip_install .
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$pip_install .[cuda]
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- name: Check disk before tests
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run: |

‎.github/workflows/lint.yml‎

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- '**.py'
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- 'pyproject.toml'
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- 'requirements*.txt'
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- 'constraints-dev.txt'
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- 'tox.ini'
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- '.pylintrc'
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- 'scripts/*.sh' # Used by this workflow
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- '**.py'
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- 'pyproject.toml'
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- 'requirements*.txt'
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- 'constraints-dev.txt'
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- 'tox.ini'
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- '.pylintrc'
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- 'scripts/*.sh' # Used by this workflow
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- name: Install tox
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run: |
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python -m pip install --upgrade pip
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python -m pip install tox tox-gh
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pip_install="python -m pip install -c constraints-dev.txt"
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$pip_install --upgrade pip
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$pip_install tox tox-gh
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- name: "${{ matrix.lint.name }}"
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run: |

‎.github/workflows/test.yml‎

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- '**.py'
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- 'pyproject.toml'
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- 'requirements**.txt'
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- 'constraints-dev.txt'
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- 'tox.ini'
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- 'scripts/*.sh' # Used by this workflow
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- '.github/workflows/test.yml' # This workflow
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- '**.py'
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- 'pyproject.toml'
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- 'requirements**.txt'
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- 'constraints-dev.txt'
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- 'tox.ini'
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- 'scripts/*.sh' # Used by this workflow
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- '.github/workflows/test.yml' # This workflow
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- name: Install dependencies
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run: |
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python -m pip install --upgrade pip
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python -m pip install tox tox-gh>=1.2
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pip_install=python -m pip install -c constraints-dev.txt"
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$pip_install --upgrade pip
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$pip_install tox tox-gh>=1.2
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- name: Run unit and functional tests with tox
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run: |

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